def test_import_from_xlsx_retrieve_desired_data(self, mocked_create_table):
mocked_create_table.return_value = 42
# import using filename
rows.import_from_xlsx(self.filename)
call_args = mocked_create_table.call_args_list[0]
self.assert_create_table_data(
call_args,
expected_meta={
"imported_from": "xlsx",
"filename": self.filename,
"sheet_name": "Sheet1",
},
)
# import using fobj
with open(self.filename, "rb") as fobj:
rows.import_from_xlsx(fobj)
call_args = mocked_create_table.call_args_list[1]
self.assert_create_table_data(
call_args,
expected_meta={
"imported_from": "xlsx",
"filename": self.filename,
"sheet_name": "Sheet1",
},
)
def test_import_from_xlsx_retrieve_desired_data(self, mocked_create_table):
mocked_create_table.return_value = 42
# import using filename
rows.import_from_xlsx(self.filename)
call_args = mocked_create_table.call_args_list[0]
self.assert_create_table_data(
call_args,
expected_meta={
"imported_from": "xlsx",
"filename": self.filename,
"sheet_name": "Sheet1",
},
)
# import using fobj
with open(self.filename, "rb") as fobj:
rows.import_from_xlsx(fobj)
call_args = mocked_create_table.call_args_list[1]
self.assert_create_table_data(
call_args,
expected_meta={
"imported_from": "xlsx",
"filename": self.filename,
"sheet_name": "Sheet1",
},
)
def test_start_and_end_row(self, mocked_create_table):
rows.import_from_xlsx(
self.filename, start_row=6, end_row=8, start_column=4, end_column=7
)
self.assertTrue(mocked_create_table.called)
self.assertEqual(mocked_create_table.call_count, 1)
call_args = mocked_create_table.call_args_list[0]
expected_data = [
[4.56, 4.56, "12%", datetime.datetime(2050, 1, 2, 0, 0)],
[7.89, 7.89, "13.64%", datetime.datetime(2015, 8, 18, 0, 0)],
[9.87, 9.87, "13.14%", datetime.datetime(2015, 3, 4, 0, 0)],
]
self.assertEqual(expected_data, call_args[0][0])
def test_import_from_xlsx_retrieve_desired_data(self, mocked_create_table):
mocked_create_table.return_value = 42
# import using filename
table_1 = rows.import_from_xlsx(self.filename)
call_args = mocked_create_table.call_args_list[0]
self.assert_create_table_data(call_args)
# import using fobj
with open(self.filename, 'rb') as fobj:
table_2 = rows.import_from_xlsx(fobj)
call_args = mocked_create_table.call_args_list[1]
self.assert_create_table_data(call_args)
def test_import_from_xlsx_retrieve_desired_data(self, mocked_create_table):
mocked_create_table.return_value = 42
# import using filename
table_1 = rows.import_from_xlsx(self.filename)
call_args = mocked_create_table.call_args_list[0]
self.assert_create_table_data(call_args)
# import using fobj
with open(self.filename, 'rb') as fobj:
table_2 = rows.import_from_xlsx(fobj)
call_args = mocked_create_table.call_args_list[1]
self.assert_create_table_data(call_args)
def get_state_data_from_google_spreadsheets(state, timeout=5):
state_spreadsheet_url = import_info_by_state(state).planilha_brasilio
state_spreadsheet_download_url = spreadsheet_download_url(
state_spreadsheet_url, "xlsx")
data = http_get(state_spreadsheet_download_url, timeout)
reports = rows.import_from_xlsx(io.BytesIO(data),
sheet_name=BOLETIM_SPREADSHEET,
force_types=FIELDS_BOLETIM)
cases = rows.import_from_xlsx(io.BytesIO(data),
sheet_name=CASOS_SPREADSHEET)
return {
"reports": [dict(row._asdict()) for row in reports if row.date],
"cases": [dict(row._asdict()) for row in cases if row.municipio],
}
def parse_boletim(self, state, data):
self.logger.info(f"Parsing {state} boletim")
try:
boletins = rows.import_from_xlsx(
io.BytesIO(data),
sheet_name="Boletins (FINAL)",
force_types={
"date": rows.fields.DateField,
"url": rows.fields.TextField,
"notes": rows.fields.TextField,
},
)
except Exception as exp:
self.errors[state].append(
("boletim", state, f"{exp.__class__.__name__}: {exp}"))
return
for boletim in boletins:
boletim = boletim._asdict()
boletim_data = [item for item in boletim.values() if item]
if not boletim_data:
continue
date = boletim["date"]
url = (boletim["url"] or "").strip()
if not url:
message = f"Boletim URL not found for {state} on {date}"
self.errors[state].append(("boletim", state, message))
else:
boletim = {
"date": date,
"state": state,
"url": url,
"notes": boletim["notes"],
}
self.logger.debug(boletim)
self.boletim_writer.writerow(boletim)
def handle(self, *args, **kwargs):
truncate = kwargs.get("truncate", False)
update_functions = [
(Dataset, dataset_update_data),
(Link, link_update_data),
(Version, version_update_data),
(Table, table_update_data),
(Field, field_update_data),
]
if truncate:
print("Deleting metadata to create new objects...")
for Model, _ in update_functions:
Model.objects.all().delete()
else:
print("WARNING: updating data only. If some field was removed "
"this change will not be reflected on your database. "
"Consider using --truncate")
self.datasets, self.tables, self.versions = {}, {}, {}
response = urlopen(settings.DATA_URL)
data = response.read()
for Model, update_data_function in update_functions:
table = rows.import_from_xlsx(
io.BytesIO(data),
sheet_name=Model.__name__,
workbook_kwargs={"read_only": False},
)
self._update_data(Model, table, update_data_function)
def test_export_to_xlsx_filename(self):
temp = tempfile.NamedTemporaryFile()
filename = temp.name + '.xlsx'
temp.close()
self.files_to_delete.append(filename)
rows.export_to_xlsx(utils.table, filename)
table = rows.import_from_xlsx(filename)
self.assert_table_equal(table, utils.table)
export_in_memory = rows.export_to_xlsx(utils.table, None)
result_fobj = BytesIO()
result_fobj.write(export_in_memory)
result_fobj.seek(0)
result_table = rows.import_from_xlsx(result_fobj)
self.assert_table_equal(result_table, utils.table)
def handle(self, *args, **kwargs):
truncate = kwargs.get("truncate", False)
update_functions = [
(Dataset, dataset_update_data),
(Link, link_update_data),
(Version, version_update_data),
(Table, table_update_data),
(Field, field_update_data),
]
data_tables_map = {}
for table in Table.with_hidden.all():
key = (table.dataset.slug, table.name)
data_tables_map[key] = table.data_table
if truncate:
print("Deleting metadata to create new objects...")
for Model, _ in update_functions:
Model.objects.all().delete()
else:
print("WARNING: updating data only. If some field was removed "
"this change will not be reflected on your database. "
"Consider using --truncate")
self.datasets, self.tables, self.versions = {}, {}, {}
response_data = http_get(settings.DATA_URL, 5)
if response_data is None:
raise RuntimeError(f"Cannot download {settings.DATA_URL}")
for Model, update_data_function in update_functions:
table = rows.import_from_xlsx(io.BytesIO(response_data),
sheet_name=Model.__name__,
workbook_kwargs={"read_only": False})
self._update_data(Model, table, update_data_function)
print("Updating DataTable...", end="", flush=True)
total_created, total_updated, total_skipped = 0, 0, 0
for table in Table.with_hidden.select_related("dataset"):
key = (table.dataset.slug, table.name)
data_table = data_tables_map.get(key, None)
if data_table is None: # create DataTable if new Table or if previous was None
data_table = DataTable.new_data_table(table, suffix_size=0)
data_table.activate()
total_created += 1
elif data_table.table != table: # Tables were truncated so previous DataTables get updated
total_updated += 1
data_table.table = table
data_table.save()
else: # Same table as before, so no need to update
total_skipped += 1
if table.filtering_fields: # avoid None
table.fields.filter(name__in=table.filtering_fields).update(
frontend_filter=True)
if table.search_fields:
table.fields.filter(name__in=table.search_fields).update(
searchable=True)
print(" created: {}, updated: {}, skipped: {}.".format(
total_created, total_updated, total_skipped))
def test_start_and_end_row(self, mocked_create_table):
rows.import_from_xlsx(self.filename,
start_row=6,
end_row=8,
start_column=4,
end_column=7)
self.assertTrue(mocked_create_table.called)
self.assertEqual(mocked_create_table.call_count, 1)
call_args = mocked_create_table.call_args_list[0]
expected_data = [
[4.56, 4.56, "12%",
datetime.datetime(2050, 1, 2, 0, 0)],
[7.89, 7.89, "13.64%",
datetime.datetime(2015, 8, 18, 0, 0)],
[9.87, 9.87, "13.14%",
datetime.datetime(2015, 3, 4, 0, 0)],
]
self.assertEqual(expected_data, call_args[0][0])
def abre_doc(self):
if self.doc_tipo == 'xls':
self.doc = rows.import_from_xls(self.doc)
elif self.doc_tipo == 'xlsx':
self.doc = rows.import_from_xlsx(self.doc)
elif self.doc_tipo == 'ods':
self.doc = rows.import_from_ods(self.doc)
else:
raise Exception('Erro ao abrir o arquivo.')
def test_issue_290_one_hundred_read_as_1(self):
result = rows.import_from_xlsx("tests/data/text_in_percent_cell.xlsx")
# As this test is written, file numeric file contents on first column are
# 100%, 23.20%, 1.00%, 10.00%, 100.00%
assert result[0][0] == Decimal("1")
assert result[1][0] == Decimal("0.2320")
assert result[2][0] == Decimal("0.01")
assert result[3][0] == Decimal("0.1")
assert result[4][0] == Decimal("1")
def test_issue_290_one_hundred_read_as_1(self):
result = rows.import_from_xlsx("tests/data/text_in_percent_cell.xlsx")
# As this test is written, file numeric file contents on first column are
# 100%, 23.20%, 1.00%, 10.00%, 100.00%
assert result[0][0] == Decimal("1")
assert result[1][0] == Decimal("0.2320")
assert result[2][0] == Decimal("0.01")
assert result[3][0] == Decimal("0.1")
assert result[4][0] == Decimal("1")
def test_import_from_xlsx_retrieve_desired_data(self, mocked_create_table):
mocked_create_table.return_value = 42
# import using filename
table_1 = rows.import_from_xlsx(self.filename)
call_args = mocked_create_table.call_args_list[0]
self.assert_create_table_data(call_args,
expected_meta={'imported_from': 'xlsx',
'filename': self.filename,
'sheet_name': 'Sheet1',})
# import using fobj
with open(self.filename, 'rb') as fobj:
table_2 = rows.import_from_xlsx(fobj)
call_args = mocked_create_table.call_args_list[1]
self.assert_create_table_data(call_args,
expected_meta={'imported_from': 'xlsx',
'filename': self.filename,
'sheet_name': 'Sheet1',})
def test_import_from_xlsx_uses_create_table(self, mocked_create_table):
mocked_create_table.return_value = 42
kwargs = {'encoding': 'iso-8859-15', 'some_key': 123, 'other': 456, }
result = rows.import_from_xlsx(self.filename, **kwargs)
self.assertTrue(mocked_create_table.called)
self.assertEqual(mocked_create_table.call_count, 1)
self.assertEqual(result, 42)
call = mocked_create_table.call_args
kwargs['meta'] = {'imported_from': 'xlsx', 'filename': self.filename, }
self.assertEqual(call[1], kwargs)
def test_issue_168(self):
temp = tempfile.NamedTemporaryFile(delete=False)
filename = "{}.{}".format(temp.name, self.file_extension)
self.files_to_delete.append(filename)
table = rows.Table(fields=OrderedDict([("jsoncolumn", rows.fields.JSONField)]))
table.append({"jsoncolumn": '{"python": 42}'})
rows.export_to_xlsx(table, filename)
table2 = rows.import_from_xlsx(filename)
self.assert_table_equal(table, table2)
def test_issue_168(self):
temp = tempfile.NamedTemporaryFile(delete=False)
filename = '{}.{}'.format(temp.name, self.file_extension)
self.files_to_delete.append(filename)
table = rows.Table(fields=
OrderedDict([('jsoncolumn', rows.fields.JSONField)]))
table.append({'jsoncolumn': '{"python": 42}'})
rows.export_to_xlsx(table, filename)
table2 = rows.import_from_xlsx(filename)
self.assert_table_equal(table, table2)
def test_export_to_xlsx_fobj(self):
temp = tempfile.NamedTemporaryFile()
filename = temp.name + '.xlsx'
temp.close()
fobj = open(filename, 'wb')
self.files_to_delete.append(filename)
rows.export_to_xlsx(utils.table, fobj)
fobj.close()
table = rows.import_from_xlsx(filename)
self.assert_table_equal(table, utils.table)
def test_import_from_xlsx_uses_create_table(self, mocked_create_table):
mocked_create_table.return_value = 42
kwargs = {'encoding': 'iso-8859-15', 'some_key': 123, 'other': 456, }
result = rows.import_from_xlsx(self.filename, **kwargs)
self.assertTrue(mocked_create_table.called)
self.assertEqual(mocked_create_table.call_count, 1)
self.assertEqual(result, 42)
call = mocked_create_table.call_args
kwargs['meta'] = {'imported_from': 'xlsx',
'filename': self.filename,
'sheet_name': 'Sheet1',}
self.assertEqual(call[1], kwargs)
def read_data(self, *args, **kwargs):
if kwargs["sheet_name"] is None:
return []
else:
kwargs["skip_header"] = False
if "end_column" not in kwargs:
# Avoid reading all columns (even if blank)
kwargs["end_column"] = 50
return rows.import_from_xlsx(self.filename,
workbook_kwargs={"data_only": True},
*args,
**kwargs)
def test_import_from_xlsx_uses_create_table(self, mocked_create_table):
mocked_create_table.return_value = 42
kwargs = {"encoding": "iso-8859-15", "some_key": 123, "other": 456}
result = rows.import_from_xlsx(self.filename, **kwargs)
self.assertTrue(mocked_create_table.called)
self.assertEqual(mocked_create_table.call_count, 1)
self.assertEqual(result, 42)
call = mocked_create_table.call_args
kwargs["meta"] = {
"imported_from": "xlsx",
"filename": self.filename,
"sheet_name": "Sheet1",
}
self.assertEqual(call[1], kwargs)
def test_import_from_xlsx_uses_create_table(self, mocked_create_table):
mocked_create_table.return_value = 42
kwargs = {"encoding": "iso-8859-15", "some_key": 123, "other": 456}
result = rows.import_from_xlsx(self.filename, **kwargs)
self.assertTrue(mocked_create_table.called)
self.assertEqual(mocked_create_table.call_count, 1)
self.assertEqual(result, 42)
call = mocked_create_table.call_args
kwargs["meta"] = {
"imported_from": "xlsx",
"filename": self.filename,
"sheet_name": "Sheet1",
}
self.assertEqual(call[1], kwargs)
def handle(self, *args, **kwargs):
self.datasets, self.tables, self.versions = {}, {}, {}
response = urlopen(settings.DATA_URL)
data = response.read()
update_functions = [
(Dataset, dataset_update_data),
(Link, link_update_data),
(Version, version_update_data),
(Table, table_update_data),
(Field, field_update_data),
]
for Model, update_data_function in update_functions:
table = rows.import_from_xlsx(
io.BytesIO(data),
sheet_name=Model.__name__,
)
self._update_data(Model, table, update_data_function)
def test_issue_290_can_read_sheet(self):
rows.import_from_xlsx("tests/data/text_in_percent_cell.xlsx")
# Before fixing the first part of #290, this would simply crash
assert True
def parse_caso(self, state, data):
self.logger.info(f"Parsing {state} caso")
casos = rows.import_from_xlsx(io.BytesIO(data),
sheet_name="Casos (FINAL)")
cities = defaultdict(dict)
for caso in casos:
caso = caso._asdict()
caso_data = [
value for key, value in caso.items()
if key != "municipio" and value is not None
]
if not caso_data:
continue
for key, value in caso.items():
if key == "municipio":
continue
elif key.startswith("confirmados_") or key.startswith(
"mortes_"):
try:
_, day, month = key.split("_")
except ValueError:
message = f"ERROR PARSING {repr(key)} - {repr(value)} - {caso}"
self.errors[state].append(("caso", state, message))
self.logger.error(message)
continue
date = f"2020-{int(month):02d}-{int(day):02d}"
if key.startswith("confirmados_"):
number_type = "confirmed"
elif key.startswith("mortes_"):
number_type = "deaths"
else:
continue
if date not in cities[caso["municipio"]]:
cities[caso["municipio"]][date] = {}
if value in (None, ""):
value = None
else:
value = str(value)
if value.endswith(".0"):
value = value[:-2]
if value.startswith("=") and value[1:].isdigit():
value = value[1:]
try:
value = int(value)
except ValueError:
message = f"ERROR converting to int: {date} {number_type} {value} {caso}"
self.errors[state].append(("caso", state, message))
self.logger.error(message)
continue
cities[caso["municipio"]][date][number_type] = value
result = []
for city, city_data in cities.items():
for date, date_data in city_data.items():
confirmed = date_data["confirmed"]
deaths = date_data["deaths"]
if confirmed is None and deaths is None:
continue
confirmed = int(confirmed) if confirmed is not None else None
deaths = int(deaths) if deaths is not None else None
row = {
"date": date,
"state": state,
"city": city if city != "TOTAL NO ESTADO" else "",
"place_type":
"city" if city != "TOTAL NO ESTADO" else "state",
"confirmed": confirmed,
"deaths": deaths,
}
confirmed = row["confirmed"]
deaths = row["deaths"]
NULL = (None, "")
if (confirmed in NULL
and deaths not in NULL) or (deaths in NULL
and confirmed not in NULL):
message = f"ERROR: only one field is filled for {date}, {state}, {city}"
self.errors[state].append(("caso", state, message))
result.append(row)
row_key = lambda row: (row["state"], row["city"], row["place_type"])
result.sort(key=row_key)
groups = groupby(result, key=row_key)
for key, row_list_it in groups:
row_list = list(row_list_it)
row_list.sort(key=lambda row: row["date"])
for order_for_place, row in enumerate(row_list, start=1):
row["order_for_place"] = order_for_place
row["is_last"] = False
if row_list:
row_list[-1]["is_last"] = True
for row in result:
if row["place_type"] == "city":
if row["city"] == "Importados/Indefinidos":
row_population = None
row_city_code = None
else:
row_city_code = get_city_code(row["state"], row["city"])
row_population = get_city_population(
row["state"], row["city"])
elif row["place_type"] == "state":
row_city_code = get_state_code(row["state"])
row_population = get_state_population(row["state"])
else:
message = f"Invalid row: {row}"
self.errors[state].append(("caso", state, message))
self.logger.error(message)
continue
row_deaths = row["deaths"]
row_confirmed = row["confirmed"]
confirmed_per_100k = (100_000 * (row_confirmed / row_population) if
row_confirmed and row_population else None)
death_rate = (row_deaths / row_confirmed if row_deaths is not None
and row_confirmed not in (None, 0) else 0)
row["estimated_population_2019"] = row_population
row["city_ibge_code"] = row_city_code
row["confirmed_per_100k_inhabitants"] = (
f"{confirmed_per_100k:.5f}" if confirmed_per_100k else None)
row["death_rate"] = f"{death_rate:.4f}"
self.logger.debug(row)
self.caso_writer.writerow(row)
def test_issue_290_textual_value_in_percent_col_is_preserved(self):
result = rows.import_from_xlsx("tests/data/text_in_percent_cell.xlsx")
# As this test is written, file contents on first column are
# 100%, 23.20%, 1.00%, 10.00%, 100.00%
assert result[5][1] == "text"
def teladduser(file, time_sleep):
"""
Log in on a Telegram account and add a users in a Supergroup from a SpreadSheet
which the account logged in is admin.
"""
# Verify if the Excel SpreadSheet was give!
if not file:
print('Need to pass the Excel SpreadSheet Filename!\n')
click.Context(teladduser).exit(code=1)
# Login on a Telegram account
try:
api_id = config('API_ID')
api_hash = config('API_HASH')
phone = config('PHONE')
client = TelegramClient(phone, api_id, api_hash)
client.connect()
if not client.is_user_authorized():
client.send_code_request(phone)
login_code = click.prompt(
'Enter the Login Code that was send to yor Telegram app',
type=int)
client.sign_in(phone, login_code)
except UndefinedValueError:
print(
'The environment variables API_ID, API_HASH or PHONE were not defined. '
'Please create a .env file with they!\n')
click.Context(teladduser).exit(code=1)
# Get all Groups of the logged user
chats = []
last_date = None
chunk_size = 100
groups = []
result = client(
GetDialogsRequest(offset_date=last_date,
offset_id=0,
offset_peer=InputPeerEmpty(),
limit=chunk_size,
hash=0))
# Get only the super group of the logged user
chats.extend(result.chats)
for chat in chats:
try:
if chat.megagroup:
groups.append(chat)
except:
continue
# Select a group to add users
for i, g in enumerate(groups):
print(f"{i + 1} - {g.title}")
g_index = click.prompt("\nEnter Number of Group you want add users",
type=int)
try:
target_group = groups[int(g_index) - 1]
except IndexError:
print(
'\nThe number selected was not of a valid Group number! Please try again!\n'
)
click.Context(teladduser).exit(code=1)
target_group_entity = InputPeerChannel(target_group.id,
target_group.access_hash)
print(f'\nReading the file {file}, this will take a while ...\n')
users_to_add = rows.import_from_xlsx(file)
# Create a new Rows Table to save processed data
fields = OrderedDict([('username_normal', rows.fields.TextField),
('nome', rows.fields.TextField),
('grupocanal', rows.fields.TextField),
('conta_de_envio', rows.fields.IntegerField),
('log', rows.fields.TextField)])
users_added = rows.Table(fields=fields)
n = 0
for i, user in enumerate(users_to_add):
if user.log:
users_added.append({
'username_normal': user.username_normal,
'nome': user.nome,
'grupocanal': user.grupocanal,
'cont_a_de_envio': user.conta_de_envio,
'log': user.log,
})
elif i >= 45:
try:
print(f'Adicionando usuário: {i} - {user.nome}')
user_to_add = client.get_input_entity(user.username_normal)
client(
InviteToChannelRequest(target_group_entity, [user_to_add]))
log = f"Usuário inserido em: {datetime.strftime(datetime.today(), '%Y-%m-%d às %H:%M:%S')}"
users_added.append({
'username_normal': user.username_normal,
'nome': user.nome,
'grupocanal': target_group.title,
'cont_a_de_envio': user.conta_de_envio,
'log': log,
})
n += 1
if n % 20 == 0:
print(
f'\nWaiting {time_sleep / 60} minutes to avoid Flood Error.\n'
)
time.sleep(time_sleep)
else:
time.sleep(time_sleep / 15)
except PeerFloodError:
print(
"\nGetting Flood Error from telegram. Script is stopping now. Please try again after some time.\n"
)
try:
rows.export_to_xlsx(users_added,
"usersAddedBeforeFloodError.xlsx")
except:
print('\nCould not write to the file provided!\n')
click.Context(teladduser).exit(code=1)
except UserPrivacyRestrictedError:
print(
"\nThe user's privacy settings do not allow you to do this. Skipping.\n"
)
except ValueError as err:
print(f'\n{err} - Skipping.\n')
except UserChannelsTooMuchError:
print(
f'\nThe user {user.username_normal} you tried to add is already in too many channels/supergroups\n'
)
except FloodWaitError as err:
print('\nHave to sleep', err.seconds, 'seconds\n')
time.sleep(err.seconds)
except KeyboardInterrupt:
print('\nExecution was interrupted by user.\n')
click.Context(teladduser).exit(code=1)
except:
traceback.print_exc()
print("\nUnexpected Error\n")
continue
else:
users_added.append({
'username_normal': user.username_normal,
'nome': user.nome,
'grupocanal': user.grupocanal,
'cont_a_de_envio': user.conta_de_envio,
'log': user.log,
})
try:
rows.export_to_xlsx(users_added, file)
except:
traceback.print_exc()
print('\nCould not write to the file provided!\n')
import rows
data = rows.import_from_xlsx("Phishlabs_Malicious_URLs.xlsx")
rows.export_to_csv(data, open("Phishlabs_Malicious_URLs.csv", "wb"))
def test_issue_290_can_read_sheet(self):
rows.import_from_xlsx("tests/data/text_in_percent_cell.xlsx")
# Before fixing the first part of #290, this would simply crash
assert True
def parse_state_file(self, response):
state = response.meta["state"]
self.logger.info(f"Parsing {state} boletim")
boletins = rows.import_from_xlsx(
io.BytesIO(response.body),
sheet_name="Boletins (FINAL)",
force_types={
"date": rows.fields.DateField,
"url": rows.fields.TextField,
"notes": rows.fields.TextField,
},
)
for boletim in boletins:
boletim = boletim._asdict()
boletim_data = [item for item in boletim.values() if item]
if not boletim_data:
continue
boletim = {
"date": boletim["date"],
"state": state,
"url": boletim["url"],
"notes": boletim["notes"],
}
self.logger.debug(boletim)
self.boletim_writer.writerow(boletim)
self.logger.info(f"Parsing {state} caso")
casos = rows.import_from_xlsx(
io.BytesIO(response.body), sheet_name="Casos (FINAL)"
)
cities = defaultdict(dict)
for caso in casos:
caso = caso._asdict()
caso_data = [
value
for key, value in caso.items()
if key != "municipio" and value is not None
]
if not caso_data:
continue
for key, value in caso.items():
if key == "municipio":
continue
elif key.startswith("confirmados_") or key.startswith("mortes_"):
try:
_, day, month = key.split("_")
except ValueError:
self.logger.error(
f"ERROR PARSING {repr(key)} - {repr(value)} - {caso}"
)
continue
date = f"2020-{int(month):02d}-{int(day):02d}"
if key.startswith("confirmados_"):
number_type = "confirmed"
elif key.startswith("mortes_"):
number_type = "deaths"
else:
continue
if date not in cities[caso["municipio"]]:
cities[caso["municipio"]][date] = {}
try:
value = int(value) if value not in (None, "") else None
except ValueError:
self.logger.error(
f"ERROR converting to int: {date} {number_type} {value} {caso}"
)
continue
cities[caso["municipio"]][date][number_type] = value
result = []
for city, city_data in cities.items():
for date, date_data in city_data.items():
confirmed = date_data["confirmed"]
deaths = date_data["deaths"]
if confirmed is None and deaths is None:
continue
confirmed = int(confirmed) if confirmed is not None else None
deaths = int(deaths) if deaths is not None else None
row = {
"date": date,
"state": state,
"city": city if city != "TOTAL NO ESTADO" else "",
"place_type": "city" if city != "TOTAL NO ESTADO" else "state",
"confirmed": confirmed,
"deaths": deaths,
}
result.append(row)
row_key = lambda row: (row["state"], row["city"], row["place_type"])
groups = groupby(result, key=row_key)
is_last = {}
for key, row_list in groups:
is_last[key] = max(row["date"] for row in row_list)
for row in result:
row["is_last"] = row["date"] == is_last[row_key(row)]
if row["place_type"] == "city":
if row["city"] == "Importados/Indefinidos":
row_population = None
row_city_code = None
else:
state_code = int(self.state_code[row["state"]])
city_code = int(self.city_code[(row["state"], row["city"])])
row_population = self.population_per_city[
(row["state"], row["city"])
]
row_city_code = f"{state_code:02d}{city_code:05d}"
elif row["place_type"] == "state":
state_code = int(self.state_code[row["state"]])
row_population = self.population_per_state[row["state"]]
row_city_code = f"{state_code:02d}"
else:
self.logger.error(f"Invalid row: {row}")
continue
row_deaths = row["deaths"]
row_confirmed = row["confirmed"]
confirmed_per_100k = (
100_000 * (row_confirmed / row_population)
if row_confirmed and row_population
else None
)
death_rate = (
row_deaths / row_confirmed if row_deaths and row_confirmed else None
)
row["estimated_population_2019"] = row_population
row["city_ibge_code"] = row_city_code
row["confirmed_per_100k_inhabitants"] = (
f"{confirmed_per_100k:.5f}" if confirmed_per_100k else None
)
row["death_rate"] = f"{death_rate:.4f}" if death_rate else None
self.logger.debug(row)
self.caso_writer.writerow(row)
def test_issue_290_textual_value_in_percent_col_is_preserved(self):
result = rows.import_from_xlsx("tests/data/text_in_percent_cell.xlsx")
# As this test is written, file contents on first column are
# 100%, 23.20%, 1.00%, 10.00%, 100.00%
assert result[5][1] == "text"
'name': u'pertence ao tema',
'type_id': TYPE_IDS[u'tema-norma'],
'id': str(uuid.uuid4()),
'weight': 1,
'directed': 1,
'properties': {
},
}
graph['edges'].append(edge)
return { 'graph': graph }
if __name__ == '__main__':
rows = rows.import_from_xlsx("dados.xlsx")
filtrado = rows
dados = estruturar_dados(filtrado)
arq = open('build/grafo-gc.json', 'w')
json.dump(generate_graph(dados), arq)
arq.close()
for uf in UFS:
filtrado2 = [r for r in filtrado if r.uf == uf]
filename = 'build/grafo-gc-' + uf + '.json'
print(filename)
arq = open(filename, 'w')
dados = estruturar_dados(filtrado2)
json.dump(generate_graph(dados), arq)
arq.close()